Background
Venous thromboembolism (VTE) is a multifactorial disease that is associated with long-term morbidity, dysfunction, and mortality. Although numerous studies have reported on the incidence and risk factors of VTE in hospitalized patients, the reported results vary due to the complexity of the disease and differences in genetic characteristics, social environment, and disease spectrum. Therefore, the aim of this study was to investigate the incidence, clinical features, and risk factors for VTE in hospitalized patients.
Methods
A cross-sectional study was conducted at Benxi Central Hospital to select patients hospitalized between January and December 2021. All patients underwent Doppler ultrasound, and medical data, including demographic characteristics, past medical history, comorbidities, and hematologic indicators, were collected from the Benxi Clinical Biobank. Chi-square tests and logistic regression analysis were employed to identify independent risk factors.
Results
A total of 1200 in-patients were eligible for inclusion in the study. The prevalence of venous thromboembolism was 21.4%. 224 patients developed DVT alone, 12 patients developed PE alone, and 14 patients developed both DVT and PE. Of the 238 patients with DVT in the lower limbs (with or without PE), distal DVT was more common than proximal DVT (64.7%vs20.2%). In multifactorial analysis, six variables are independent risk factors for VTE:Diabetes,OR,1.659,(1.100-2.501, P = 0.016);History of confirmedVTE,OR,6.497,(3.505–12.041,P = 0.000);Central venous catheterization,OR,2.605,(1.583–4.289,P = 0.000);Age,OR,1.035,(1.022–1.048,P = 0.000);HGB,OR,0.993,(0.987-1.000, P = 0.042);Unilateral limb pitting oedema,OR,5.307,(3.506–8.033, P = 0.000);Bilateral limb pitting oedema,OR,1.701,(1.081–2.676,P = 0.022).
Conclusion
The incidence of VTE among hospitalized patients in Benxi region is relatively high. Identifying relevant risk factors allows for early screening of at-risk populations. In order to reduce prevalence, and more prospective studies are needed to comprehensively develop individualised clinical prediction tools for VTE.